code: def __init__(
      self,
      low_channels,
      high_channels,
      out_channels,
      nclass,
      height=None,
      width=None,
      norm_layer=nn.BatchNorm,
      **kwargs,
  ):
      super(CascadeFeatureFusion, self).__init__()
      self._up_kwargs = {"height": height, "width": width}
  
      with self.name_scope():
          self.conv_low = nn.HybridSequential()
          with self.conv_low.name_scope():
              self.conv_low.add(
                  nn.Conv2D(
                      in_channels=low_channels,
                      channels=out_channels,
                      kernel_size=3,
                      padding=2,
                      dilation=2,
                      use_bias=False,
                  )
              )
              self.conv_low.add(norm_layer(in_channels=out_channels))
  
          self.conv_hign = nn.HybridSequential()
          with self.conv_hign.name_scope():
              self.conv_hign.add(
                  nn.Conv2D(
                      in_channels=high_channels,
                      channels=out_channels,
                      kernel_size=1,
                      use_bias=False,
                  )
              )
              self.conv_hign.add(norm_layer(in_channels=out_channels))
  
          self.conv_low_cls = nn.Conv2D(
              in_channels=out_channels,
              channels=nclass,
              kernel_size=1,
              use_bias=False,
          )
  
imports: from __future__ import division
  from mxnet.gluon import nn
  from mxnet.context import cpu
  from mxnet.gluon.nn import HybridBlock
  from gluoncv.model_zoo.segbase import SegBaseModel
  from gluoncv.model_zoo.pspnet import _PSPHead
label_desc: Use image node_id 1 to create a new CascadeFeatureFusion object from inherited base classes: HybridBlock with example: obj = CascadeFeatureFusion(low_channels, high_channels, out_channels, nclass, height, width, norm_layer)